This repository is a curated list of academic research and industrial materials focused on Artificial Intelligence for IT Operations (AIOps). It serves as a comprehensive resource for researchers and practitioners looking to leverage AI for improving IT operational efficiency, reliability, and performance.

How It Works

The list categorizes resources across various AIOps sub-domains, including anomaly detection, root cause analysis, incident management, and performance monitoring. It highlights key papers, tools, benchmarks, datasets, and companies actively involved in the AIOps space, providing a broad overview of the field's landscape and advancements.

Quick Start & Requirements

This is a curated list, not a software project. No installation or execution is required. The repository provides links to external resources, tools, and datasets.

Highlighted Details

• Extensive coverage of academic papers from top-tier conferences (ICSE, OSDI, NSDI, etc.) and journals.
• Curated list of open-source tools for log analysis, anomaly detection, fault injection, and performance monitoring.
• Includes links to benchmark datasets and real-world data sources for AIOps research.
• Features resources on the application of Large Language Models (LLMs) in AIOps, including root cause analysis and incident mitigation.

Maintenance & Community

The list appears to be actively maintained, with recent additions and updates. It includes contributions from researchers at prominent institutions like CUHK, Tsinghua University, Microsoft, and JHU. Links to relevant communities or discussion forums are not explicitly provided within the README.

Licensing & Compatibility

The repository itself is a list of links and does not have a specific software license. The licenses of the linked tools, papers, and datasets vary and should be checked individually.

Limitations & Caveats

As a curated list, the depth of coverage for each topic can vary. The repository does not provide direct access to the resources but links to them, requiring users to navigate to external sites.